Healthcare Analytics Regression in R
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Linear and logistic regression models can be created using R, the open-source statistical computing software. In this course, biotech expert and epidemiologist Monika Wahi uses the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset to show you how to perform a forward stepwise modeling process. Monika shows you how to design your research by considering scientific plausibility selecting a hypothesis. Then, she takes you through the steps of preparing, developing, and finalizing both a linear regression model and a logistic regression model. She also shares techniques for how to interpret diagnostic plots, improve model fit, compare models, and more. Topics include: Dealing with scientific plausibility Selecting a hypothesis Interpreting diagnostic plots Working with indexes and model metadata Working with quartiles and ranking Making a working model Improving model fit Performing linear regression modeling Performing logistic regression modeling Performing forward stepwise regression Estimating parameters Interpreting an odds ratio Adding odds ratios to models Comparing nested models Presenting and interpreting the final model